Interested in this AI/ML Engineer role at Sandoz?
Apply Now →About This Role
Sandoz continues to go through an exciting and transformative period as a global leader and pioneering provider of sustainable Biosimilar and Generic medicines. As we continue down this new and ambitious path, unique opportunities will present themselves, both professionally and personally.
Joinus, the future is ours to shape!
PositionLocation:
This position will belocated at the Princeton, NJ US Headquarters site. Our Sandoz flexible hybrid working approach allows US office-based employees to work up to 50% of their monthly workday remotely. This role will not have the ability to belocated remotely. Preference will be given to local candidates not requiring relocation.
Mustbe authorized to work in the U.S. U.S. work visa sponsorship is not available for this role now or in the future.
This role serves as the primary business leader for AI strategy, transformation, and enablement, partnering across Commercial, Supply Chain, Finance, Regulatory, P, Enterprise Operational Excellence, and Information Technology to identify, prioritize, and implement high-value AI opportunities that enhance decision-making, improve business processes, and enable new ways of working. Operating through influence rather than direct authority, the position works closely with Global IT and the North America Technology Lead to translate business priorities into scalable AI-enabled solutions while ensuring alignment with global governance and compliance standards.
The role is accountable for establishing, maintaining, and governing a portfolio of AI initiatives across North America, ensuring resources are focused on the highest-value opportunities and that investments deliver measurable business outcomes. This is a highly visible and strategically important leadership role with broad exposure across the North America organization and Global functions. Reporting directly to the SVP, Strategy& Growth – North America, the role serves as a trusted advisor to senior leaders and helps shape the North America AI agenda to drive growth, improve performance, and enhance decision-making across the enterprise.
Key Responsibilities
AI Strategy, Prioritization& Value Creation
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Develop and maintain the North America AI strategy and roadmap aligned with business priorities, operational objectives, and Sandoz's growth ambitions.
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Establish, prioritize, and manage a portfolio of AI initiatives across North America, balancing business value, feasibility, risk, and resource availability.
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Partner with business leaders to identify and advance high-value AI use cases that improve decision quality, productivity, forecasting accuracy, and operational performance.
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Track value realization and portfolio performance to ensure AI investments deliver measurable business outcomes.
AI Adoption, Capability Building& Change Leadership
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Serve as the primary champion for AI adoption across North America, promoting responsible and practical use of AI tools in everyday work.
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Increase organizational AI literacy through training, enablement, and change management initiatives that enhance employee capability and confidence.
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Foster a culture of innovation and continuous improvement by redesigning and embedding AI-enabled ways of working across functions.
Cross-Functional Partnership& Solution Delivery
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Partner with Enterprise Operational Excellence to identify opportunities where AI can simplify processes, reduce inefficiencies, and accelerate business performance.
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Collaborate with Global IT and the North America Technology Lead to prioritize, resource, and deliver AI solutions that support North America business objectives.
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Influence and align stakeholders across Commercial, Supply Chain, Operations, Finance, Quality, Regulatory, and other functions to drive successful implementation and adoption.
Governance, Risk& Compliance
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Ensure all AI initiatives comply with global governance, cybersecurity, privacy, compliance, and responsible AI requirements.
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Assess and mitigate risks associated with AI adoption while balancing innovation and business value.
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Advise North America leadership on AI opportunities, emerging technologies, investment priorities, and the strategic implications of AI for the business.
Whatyou’ll bring to the role:
RequiredQualifications:
Education& Experience:
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Bachelor's degree in business, Technology, Engineering, Data Science, Operations, or a related field.
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10+ years of experience in strategy, operations, digital transformation, operational excellence, technology, consulting, or related leadership roles.
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Practical experience applying AI, automation, analytics, or digital transformation technologies to solve business problems and improve operational performance, with sufficient technical understanding to evaluate solution feasibility and implementation requirements.
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Working knowledge of AI platforms, large language models (LLMs), AI agents, orchestration frameworks, and human-in-the-loop design principles.
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Demonstrated success leading enterprise-wide initiatives through influence, collaboration, and stakeholder engagement.
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Strong understanding of artificial intelligence, advanced analytics, digital technologies, and business process improvement.
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Exceptional communication, facilitation, change management, and executive stakeholder management skills.
Preferred
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Advanced degree (MBA, MS, Engineering, Data Science, or related discipline).
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Experience in pharmaceutical, healthcare, biotechnology, or other highly regulated industries.
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Experience managing portfolios of strategic initiatives and driving cross-functional implementation through matrixed teams.
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Experience leading or working closely with technical teams to deliver technology-enabled business solutions.
Success Measures
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Increased adoption and effective utilization of approved AI tools across North America.
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Faster and more accurate decision-making across key business functions.
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Improved forecasting accuracy and operational predictability.
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Enhanced AI literacy, capability, and productivity across the workforce.
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Delivery of measurable business value through a prioritized portfolio of AI-enabled solutions.
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Strong adherence to Sandoz AI governance, compliance, and risk management standards.
You’ll Receive:
Sandoz offers a generous employee benefits package that includes a competitive salary, health insurance coverage for medical, prescription drugs, dental and vision, a generous company match for retirement savings accounts, and generous paid time off as detailed below.We also follow a hybrid work policy that combines a mix of in-person and remote work to allow our employees flexibility.
The pay range for this position at commencement of employment is expected to be between$176,400 -$327,600USD/year.Starting salary is typically positioned at the lower end of the range for those new to level and / or with less functional depth.Further, final pay determinations will depend onvarious factors, including, but not limited to experience level, knowledge,skills and abilities.Consideration is also taken to ensure that internal equity ismaintained.The total compensation package for this positionincludes restricted stock units, and discretionary awards in addition to health insurance (medical, prescription drug, dental, and vision); life, accident and disability insurance; 401(k) contributions; tuition reimbursement; adoption and surrogacy reimbursement; and fitness program reimbursement. Employees are also provided with paid sick time, care time, vacation, holidays, and personal days off.
If hired, employee will be in an “at-will position” and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.
On September 30, 2021, Sandoz entered into a 5-year Corporate Integrity Agreement. Certain positions will have responsibilities to support the execution and adherence to CIA obligations, CIA-related deliverables, and any relevant audit,monitoring or Independent Review Organization (IRO) remediation.
Sandoz - Notice at Collection to Employees Applicants 4.15.24[16].pdf
Why Sandoz?
Sandoz is the global leader in Biosimilar and Generic medicines, a segment of the healthcare industry that delivers 80% of the world’s medicines at 30% of the cost, touching the lives of more than 1 billion people across 100+ countries! While we are proud of our achievements, we have an ambition to do more so that everyone can achieve the basic humanright of good health.
With investments in new development capabilities, production sites, new acquisitions, and partnerships, wehave the opportunity to shape the future of Sandoz and help more patients gain access to low-cost, high-quality medicines, sustainably.
Our momentum is powered by an open, collaborative culture driven by our talented and ambitious colleagues, who, in return for applying theirskills experience an agile and collegiate environment with impactful, flexible-hybrid careers, where diversity is welcomed and where personal growth is supported!
Join us, help us make healthcare fairer and faster.
Commitment to Diversity& Inclusion:
We are committed to building an outstanding, inclusive work environment and diverseteams representative of the patients and communities we serve.
Sandoz EEO Statement:
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.
Sandoz Reasonable Accommodations Statement:
Sandoz, Inc. is committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the application process, or to perform the essential functions of a position, please send an email [email protected] or call 1-609-422-4098 and let us know the natureof your request and your contact information. Please include the job requisition number in your message.
#Sandoz
Salary Context
This $176K-$327K range is above the 75th percentile for AI/ML Engineer roles in our dataset (median: $180K across 2094 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 10,827 AI roles we're tracking, AI/ML Engineer positions make up 77% of the market. At Sandoz, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills in Demand for This Role
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $212,160 based on 13,809 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($252K) sits 19% above the category median. Disclosed range: $176K to $327K.
Across all AI roles, the market median is $213,480. Top-quartile compensation starts at $264,111. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($266,050) and AI Engineering Manager ($253,461). By seniority level: Entry: $112,320; Mid: $193,200; Senior: $230,000; Director: $272,300; VP: $236,450.
Sandoz AI Hiring
Sandoz has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Princeton, NJ, US. Compensation range: $327K - $327K.
Location Context
Across all AI roles, 6% (665 positions) offer remote work, while 10,097 require on-site attendance. Top AI hiring metros: New York (3,262 roles, $221,000 median); San Francisco (2,767 roles, $260,600 median); Los Angeles (1,585 roles, $210,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 10,827 open positions tracked in our dataset. By seniority: 122 entry-level, 5,256 mid-level, 3,922 senior, and 1,527 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (665 positions). The remaining 10,097 roles require on-site or hybrid attendance.
The market median for AI roles is $213,480. Top-quartile compensation starts at $264,111. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($266,050 median, 70 roles); AI Engineering Manager ($253,461 median, 58 roles); Research Engineer ($252,000 median, 476 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 10,827 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (8,288), AI Software Engineer (548), AI Product Manager (471). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (122) are outnumbered by mid-level (5,256) and senior (3,922) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,527 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (665 positions), with 10,097 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,480. Top-quartile roles start at $264,111, and the 90th percentile reaches $318,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $266,050 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,093 postings), Aws (1,100 postings), Azure (910 postings), Rag (863 postings), Gcp (680 postings), Pytorch (549 postings), Claude (532 postings), Kubernetes (511 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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